---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: "black-forest-labs/FLUX.1-dev"
pipeline_tag: text-to-image
instance_prompt: PCCLFGRTV

library_name: diffusers

inference:
  parameters:
    width: 1024
    height: 1024
widget:
- text: "PCCLFGRTV style. Superman feeding a cow"
  example_title: "Superman with a cow"
  output:
    url: "samples/superman-cow.png"

- text: "This is a Cubist-style painting that employs geometric shapes, muted colors, and overlapping forms to depict a still life scene. PCCLFGRTV style. Night scene. a raining Gotham city. Batman is facing the camera."
  example_title: "Batman in Gotham city"
  output:
    url: "samples/batman-gotham-city.png"

- text: "PCCLFGRTV style. Spiderman in a rural scene."
  example_title: "Spiderman"
  output:
    url: "samples/spiderman.png"
---
---

# Flux Lora Piccoli Figurative

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train


## Trigger words
You should use `PCCLFGRTV` to trigger the image generation.


## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('lichorosario/flux-lora-piccoli', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)